paragraph4
.1em plus1ex minus.2ex-.5emNearest Neighbor Search
At test time in the ZSL, given a test video, we predict a seen class and compute or retrieve its semantic representation. After rectification, we find the nearest neighbor in the set of unseen classes.
In the GZSL task, class predictions may be of seen or unseen classes. Thus, we first use a bias detector [1]} which helps us detect if the video belongs to the seen or unseen class. If it belongs to a seen class, we predict the class directly from our model, else we proceed as in ZSL.
